{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Single server\n",
    "\n",
    "This example is from Choi, Kang: Modeling and Simulation of Discrete-Event Systems, p. 18. It describes a single server system. The event graph given is:\n",
    "\n",
    "![single server](../src/images/sserver.svg)\n",
    "\n",
    "1. Initially there are no jobs in the queue $Q$ and the machine $M$ is idle.\n",
    "2. Jobs arrive with an inter-arrival-time $t_a$ and are added to $Q$.\n",
    "3. If $M$ is idle, it loads a job, changes to busy and executes the job with service time $t_s$.\n",
    "4. After that it unloads the job, changes to idle and, if $Q$ is not empty, it loads the next job."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementing it \n",
    "\n",
    "We use this simple example for illustration of how it can be modeled, simulated and analyzed using `DiscreteEvents.jl`. First we have to import the necessary modules:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Plots.PyPlotBackend()"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using DiscreteEvents, Random, Distributions, DataFrames, Plots, LaTeXStrings, Unitful\n",
    "import Unitful: minute\n",
    "pyplot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have to define some data structures, variables and a function for collecting stats:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "stats (generic function with 1 method)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "abstract type MState end\n",
    "\n",
    "struct Idle <: MState end\n",
    "struct Busy <: MState end\n",
    "\n",
    "mutable struct Job\n",
    "    no::Int64\n",
    "    ts::Float64\n",
    "    t1::Float64\n",
    "    t2::Float64\n",
    "    t3::Float64\n",
    "end\n",
    "\n",
    "mutable struct Machine\n",
    "    state::MState\n",
    "    job\n",
    "end\n",
    "\n",
    "Q = Job[]   # input queue\n",
    "S = Job[]   # stock\n",
    "M = Machine(Idle(), 0)\n",
    "df = DataFrame(time = Float64[], buffer=Int[], machine=Int[], finished=Int[])\n",
    "count = 1\n",
    "printing = true\n",
    "\n",
    "stats() = push!(df, (τ().val, length(Q), M.state == Busy() ? 1 : 0, length(S)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can model our system **activity-based** und therefore implement functions for the three main activities (arrive, load, unload), which call each other during simulation. \n",
    "\n",
    "We use the arrival-function for modeling arrival rate $t_a$ with an Erlang and service time $t_s$ with a Normal distribution. We determine the capacity of the server with a $c$ variable such that $c > 1$ gives us overcapacity and $c = 1$ means that mean service time equals mean arrival rate $\\bar{t_s} = \\bar{t_a}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "unload (generic function with 1 method)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function arrive(μ, σ, c)\n",
    "    @assert μ ≥ 1 \"μ must be ≥ 1\"\n",
    "    ts = rand(Normal(μ, σ))/c\n",
    "    job = Job(count, ts, τ().val, 0, 0)\n",
    "    global count += 1\n",
    "    push!(Q, job)\n",
    "    ta = rand(Erlang())*μ\n",
    "    event!(𝐶, SimFunction(arrive, μ, σ, c), after, ta)  # we schedule the next arrival\n",
    "    printing ? println(τ(), \": job $(job.no) has arrived\") : nothing # τ() is the current time\n",
    "    if M.state == Idle()\n",
    "        load()\n",
    "    else\n",
    "        stats()\n",
    "    end\n",
    "end\n",
    "\n",
    "function load()\n",
    "    M.state = Busy()\n",
    "    M.job = popfirst!(Q)\n",
    "    M.job.t2 = τ().val\n",
    "    event!(𝐶, SimFunction(unload), after, M.job.ts)  # we schedule the unload\n",
    "    printing ? println(τ(), \": job $(M.job.no) has been loaded\") : nothing\n",
    "    stats()\n",
    "end\n",
    "\n",
    "function unload()\n",
    "    M.state = Idle()\n",
    "    M.job.t3 = τ().val\n",
    "    push!(S, M.job)\n",
    "    printing ? println(τ(), \": job $(M.job.no) has been finished\") : nothing\n",
    "    stats()\n",
    "    M.job = 0\n",
    "    if !isempty(Q)\n",
    "        load()\n",
    "    end\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to collect `stats()` at a sample rate of 0.1:  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "setUnit!(𝐶, minute)\n",
    "sample_time!(𝐶, 0.1)  # we determine the sample rate\n",
    "DiscreteEvents.sample!(𝐶, SimFunction(stats));  # we register stats() as sampling function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We assume now that the capacity equals the arrivals and provide no overcapacity.  Therefore  we start with one arrival and $\\mu = 5$, $\\sigma = 1/5$ and $c = 1$ and let our system run for 30 minutes (let's assume our time unit be minutes):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0 minute: job 1 has arrived\n",
      "0.0 minute: job 1 has been loaded\n",
      "4.947453062901819 minute: job 1 has been finished\n",
      "8.515206032139384 minute: job 2 has arrived\n",
      "8.515206032139384 minute: job 2 has been loaded\n",
      "8.56975795472613 minute: job 3 has arrived\n",
      "8.666481204359087 minute: job 4 has arrived\n",
      "10.338522593089287 minute: job 5 has arrived\n",
      "11.021099411385869 minute: job 6 has arrived\n",
      "13.267881315092211 minute: job 7 has arrived\n",
      "13.703372376147774 minute: job 2 has been finished\n",
      "13.703372376147774 minute: job 3 has been loaded\n",
      "18.726550601155594 minute: job 3 has been finished\n",
      "18.726550601155594 minute: job 4 has been loaded\n",
      "19.55941423914075 minute: job 8 has arrived\n",
      "19.58302738045451 minute: job 9 has arrived\n",
      "20.543366077813385 minute: job 10 has arrived\n",
      "22.752994020639125 minute: job 11 has arrived\n",
      "23.563550850400553 minute: job 4 has been finished\n",
      "23.563550850400553 minute: job 5 has been loaded\n",
      "23.960464112286694 minute: job 12 has arrived\n",
      "26.84742108339802 minute: job 13 has arrived\n",
      "28.18186102251928 minute: job 5 has been finished\n",
      "28.18186102251928 minute: job 6 has been loaded\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\"run! finished with 17 clock events, 299 sample steps, simulation time: 30.0\""
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Random.seed!(2019)\n",
    "arrive(5, 1/5, 1)  # we schedule the first event\n",
    "run!(𝐶, 30)        # and run the simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using our collected data, we can plot the simulation model trajectory:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function trajectory_plot()\n",
    "    p1 = plot(df.time, df.buffer, ylabel=\"buffer\", fill=(0,0.1,:blue))\n",
    "    p2 = plot(df.time, df.machine, ylabel=\"machine\", fill=(0,0.1,:blue))\n",
    "    p3 = plot(df.time, df.finished, xlabel=\"time [min]\", ylabel=\"stock\", fill=(0,0.1,:blue))\n",
    "    plot(p1,p2,p3, layout=(3,1), legend=false)\n",
    "end\n",
    "trajectory_plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems that the queue increases over time. Thus we are interested in the behaviour of our model over a longer time. Therefore we switch off printing and continue the simulation for further 970 \"minutes\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "printing = false\n",
    "run!(𝐶, 970)        # continue the simulation\n",
    "trajectory_plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems that buffer size is increasing ever more over time. In the plot now machine load and stock aren't very instructive, so let's compare lead time $W$ and number of jobs in the system $L$ = buffer_size + machine_load:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function WvsL() # get more instructive info from simulation run\n",
    "    t = [j.t1 for j ∈ S]\n",
    "    W = [j.t3 - j.t1 for j ∈ S]\n",
    "    ts = [j.t3 - j.t2 for j ∈ S]\n",
    "    subs = [i ∈ t for i ∈ df.time]\n",
    "    L = (df.buffer + df.machine)[subs]\n",
    "    l = df.machine[subs]\n",
    "    DataFrame(time=t, load=l, W=W, L=L, ts=ts)\n",
    "end\n",
    "d = WvsL()\n",
    "plot(d.time, d.W, label=\"W [min]\", xlabel=\"time [min]\", lw=2, legend=:topleft, title=\"L and W over time\")\n",
    "plot!(d.time, d.L, label=\"L [jobs]\", lw=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lead time $W$ and unfinished jobs $L$ are clearly increasing, the system is not stationary and gets jammed over time. Let's collect some stats:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Lm = 16.21105527638191, Wm = 78.8196419189297, η = 0.9778719397363466, tsm = 5.003771234356064)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "collect_stats() =\n",
    "    (Lm = mean(d.L), Wm = mean(d.W), η = mean(df.machine), tsm = mean(d.ts))\n",
    "collect_stats()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Server load of $\\overline{η} ≈ 98\\%$ is great, but the mean queue length $\\overline{L}$ of 16 and mean lead time $\\overline{W} ≈ 79$ min are way too long for a service time of $t_s ≈ 5$ min. So let's analyze the dependency of mean queue length $\\overline{L}$ on server capacity $c$. For that we can manipulate the server capacity in the arrival function and collect the results in a table:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = DataFrame(c=Float64[], Lm=Float64[], Wm=Float64[], η=Float64[], tsm=Float64[])\n",
    "for c ∈ collect(0.97:0.01:1.7)\n",
    "    global Q = Job[]   # input queue\n",
    "    global S = Job[]   # stock\n",
    "    global M = Machine(Idle(), 0)\n",
    "    global df = DataFrame(time = Number[], buffer=Int[], machine=Int[], finished=Int[])\n",
    "    global count = 1\n",
    "    \n",
    "    reset!(𝐶, unit=minute)                            # reset 𝐶\n",
    "    sample_time!(𝐶, 1)                   # set sample rate to 1\n",
    "    DiscreteEvents.sample!(𝐶, SimFunction(stats))   # register the stats() function for sampling\n",
    "    \n",
    "    Random.seed!(2019)\n",
    "    arrive(5, 1/5, c)\n",
    "    run!(𝐶, 1000)                        # run another simulation for 1000 \"min\"\n",
    "    global d = WvsL()\n",
    "    s = collect_stats()\n",
    "    push!(df1, (c, s.Lm, s.Wm, s.η, s.tsm))\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can look at it in a scatter plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scatter(df1.c, df1.Wm, title=L\"\\overline{W}\"*\" and \"*L\"\\overline{L}\"*\" over server capacity\", \n",
    "    xlabel=\"server capacity\", marker = (:o, 3, 0.4, :blue), label=L\"\\overline{W}\"*\" [min]\")\n",
    "scatter!(df1.c, df1.Lm, marker = (:x, 4), label=L\"\\overline{L}\"*\" [jobs]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need to increase server capacity much in order to avoid long queues and waiting times."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How about Little's law?\n",
    "\n",
    "$\\overline{W}$ and $\\overline{L}$ seem to be proportional. This is stated by [Little's law](https://en.wikipedia.org/wiki/Little%27s_law): \n",
    "\n",
    "$$L = \\lambda\\times W$$\n",
    "\n",
    "for stationary systems with $\\lambda$ = arrival rate. In our case $\\lambda = t_a = 5$. Let's look at it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scatter(df1.Lm, df1.Wm, xlabel=L\"\\overline{L}\"*\" [jobs]\", ylabel=L\"\\overline{W}\"*\" [min]\", \n",
    "    marker = (:o, 4, 0.4, :blue), label=\"data\", title=\"Little's law\", legend=:topleft)\n",
    "plot!(df1.Lm, df1.Lm*5, label=\"theory \"*L\"(\\overline{L}\\times 5)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data seems not quite to fit theory. Reason is that the system is not stationary. But for a first approach, Little's law seems not to be a bad one. In order to analyze stability and [stationarity](https://en.wikipedia.org/wiki/Stationary_process) and to improve, we could refine our analysis by taking only the second half of the simulation data or by doing more simulation runs and having some fun with `Sim.jl` ...\n",
    "\n",
    "## 😄\n",
    "\n",
    "pb, 2019-11-01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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